journal article·2007-03Open access

Analysis of reinforced concrete columns retrofitted with fiber reinforced polymer lamina

Baris Binici, Khalid M. Mosalam

Composites Part B: Engineering· Volume 38· Issue 2

Abstract

Abstract Fiber reinforced polymer (FRP) lamina have been used widely in the last decade to enhance strength and deformation capacity of deficient reinforced concrete (RC) columns. Seismic assessment and retrofit of existing columns in buildings and bridge piers necessitate accurate prediction of the available deformation capacity. In this study, a new analytical model is proposed to represent potential plastic hinge regions of RC columns prior to and after FRP retrofit. A recently developed variable confined concrete representation is employed within the framework of fiber-discretized frame elements to model the compression zone of the FRP-confined region. Confinement distribution within this region is included through the use of a bond model, whereas the effect of lap splices are considered using an effective steel strain concept. Comparisons of analytical estimates with experimentally measured response show that the proposed model is capable of capturing essential features of the response such as strength degradation due to lap splice slippage, and failure due to FRP rupture. Furthermore, a detailed sensitivity study is conducted to determine the parameters whose uncertainty significantly affects the behavior. It is observed that, in estimating the response of existing deficient columns, parameters such as plastic hinge length, concrete strength and splice length are important sources of uncertainty. While for FRP-retrofitted columns, parameters such as jacket stiffness, dilatation strain at splice failure and yield strength of the reinforcing bars are more important sources of uncertainty.
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Research context

OpenAlex topics: Structural Behavior of Reinforced Concrete · Concrete Corrosion and Durability · Structural Response to Dynamic Loads

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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